Abstract

The implicit association test (IAT) measures bias towards often
controversial topics (race/religion), while newspapers typically take strong
positive/negative stances on such issues. In a pre-registered study, we developed
and administered an immigration IAT to readers of the Daily Mail (typically
anti-immigration) and Guardian (typically pro-immigration) newspapers. IAT
Materials were constructed based on co-occurrence frequencies from each
newspapers' website for immigration-related terms (migrant) and positive/negative
attributes (skilled/unskilled). Target stimuli showed stronger negative
associations with immigration concepts in the Daily Mail corpus compared to the
Guardian corpus, and stronger positive associations in the Guardian corpus
compared to the Daily Mail. Consistent with these linguistic distributional
differences, Daily Mail readers exhibited a larger IAT bias, revealing stronger
negative associations to immigration concepts compared to Guardian readers. This
difference in overall bias was not explained by other variables, and raises the
possibility that exposure to biased language contributes to biased implicit
attitudes.